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Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'06)
Data Clustering of Tolerance Space in MATLAB
Las Vegas, Nevada
June 19-June 20
ISBN: 0-7695-2611-X
Fu-Shing Sun, Ball State University, Muncie, IN
Chun-Hung Tzeng, Ball State University, Muncie, IN
This paper introduces an abstract data clustering model and its implementation in MATLAB. The similarity in the model is an arbitrary reflexive and symmetric binary relation, called a tolerance relation. A space with a tolerance relation is called a tolerance space. This paper considers representative clusterings of a tolerance space. Such a clustering is a set of representatives in the space and each element in the space is similar to one of the representatives. In general, a representative clustering is not a partition of the space. A heuristic method to compute a sub-minimal representative clustering is implemented in MATLAB. Finally, the paper demonstrates the clusterings using an example dataset.
Citation:
Fu-Shing Sun, Chun-Hung Tzeng, "Data Clustering of Tolerance Space in MATLAB," snpd-sawn, pp.120-126, Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'06), 2006
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